en.Wedoany.com Reported - Recently, Zhang Xiaoniu's team from Pingdingshan Tianan Coal Industry Co., Ltd. in Henan Province, China, proposed a coordinated optimization strategy for source-grid-load-storage in coal mine microgrids based on the APSA adaptive algorithm. Primary security loads in coal mines, such as main underground ventilation fans, gas drainage pumps, and drainage pumps, require continuous power supply. Long power supply lines lead to frequent voltage fluctuations, and the intermittent nature of wind and photovoltaic power output further increases scheduling difficulty. Traditional optimization methods, which aim to minimize operating costs as a single objective and use a static calculation framework, struggle to adapt to real-time changes on-site. Drawing inspiration from industrial PID control, the researchers upgraded the classic PSA algorithm to the APSA algorithm, constructing an intelligent scheduling system for coal mine power grids that can perceive real-time status and dynamically adjust parameters.

This strategy employs a three-layer nested solution framework to control operating costs, renewable energy consumption rate, and voltage deviation respectively, achieving a layer-by-layer contraction of the solution space. In a practical test on a coal mine microgrid, the APSA algorithm reduced daily operating costs from 185,000 yuan to 102,000 yuan, increased the renewable energy consumption rate from 69% to 98.5%, and decreased the comprehensive voltage deviation from 4.5 p.u. to 1.8 p.u. Compared to commonly used solutions like the Particle Swarm Optimization algorithm and Genetic Algorithm, the APSA algorithm demonstrated superior performance in convergence speed, solution accuracy, and operational stability, with zero fluctuation in results over 30 consecutive runs. During the daytime when wind and solar power generation is sufficient, the energy storage system automatically charges. During the evening load peak, the energy storage system discharges, working in conjunction with flexible load shifting to achieve peak shaving and valley filling.

With the advancement of the "dual carbon" goals, coal mines are transitioning from mere energy extraction units to integrated energy systems combining "source-grid-load-storage." The successful application of the APSA algorithm provides a technical reference for the scheduling optimization of coal mine microgrids and offers a replicable solution for the green transformation of high-energy-consuming industries. The research findings of Zhang Xiaoniu's team indicate that by optimizing the coordinated scheduling of source-grid-load-storage through intelligent algorithms, coal mines can significantly reduce operating costs and improve the level of green electricity consumption while ensuring power supply security.

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